The sampling theorem is for static signals and perfect filters. Turns out, music isn't static. Once you have transients in the program, you need higher bandwidth or you will end up with phasing effects (time domain aliasing.) This is plain from the math!
Filters are also not perfect (but good oversampling filters are not the weakest link)
Further, even perfectly dithered 16 bit data can't go 20 dB below the quantization floor, unless you give up on frequency response on the high end. Again, this is plain math.
With a calibrated 105 dB low-distortion sound system, in a quiet room, I can hear imperfections from 16 bit, 44 kHz material, especially in soft flutes and triangle type percussion. Of course, D class amplifiers, and MP3 encoding, do worse things to the signal, so let's start there. But 20 bit, 96 kHz (or at least 64 kHz) are scientifically defensible, when analyzing the math and the physics involved. No snake oil needed!
Filters are also not perfect (but good oversampling filters are not the weakest link)
Further, even perfectly dithered 16 bit data can't go 20 dB below the quantization floor, unless you give up on frequency response on the high end. Again, this is plain math.
With a calibrated 105 dB low-distortion sound system, in a quiet room, I can hear imperfections from 16 bit, 44 kHz material, especially in soft flutes and triangle type percussion. Of course, D class amplifiers, and MP3 encoding, do worse things to the signal, so let's start there. But 20 bit, 96 kHz (or at least 64 kHz) are scientifically defensible, when analyzing the math and the physics involved. No snake oil needed!